Grant Number: 1R01GM103841-01A1 Principal Investigator(s): Adam G. Schrum, PHD Project Title: Measuring multiprotein assemblies that drive biological signals Award e-mailed to: researchadmin@mayo.edu Project Period: 04/01/2013 ? 03/31/2018 Current Date: April 15, 2015 Modified Project Summary/Abstract Section Proteins interact with each other to form complexes, and these complexes can be dynamic and interchanging as they relay biological signals. However, despite their central importance to biology and disease, protein complexes can be difficult to visualize and assess. There are even more technological barriers to analyzing protein complexes when they originate from non-genetically engineered human cells, such as those that would be provided in clinical patient samples. Currently, because physiologic protein complex profiles are virtually unobtainable, clinical practice cannot use them to assist in human health endeavors. We propose to advance a new strategy by mounting a new assay platform, MIF, to bring the analysis of physiologic, human protein complex profiles online. We have already learned how to overcome and control for the technical hurdles, leading us to launch MIF by targeting 21 human proteins that can participate in 231 inter-protein associations (Specific Aim 1). MIF will allow for analysis of small samples and high-throughput formatting, favoring its adoptability for primary human samples originating from clinical patients. Data analysis will involve the generation of Bioinformatics strategies (Specific Aim 2) to focus on multiplicity of proteins in shared complexes detected by exposed surface epitopes, to assess network protein associations. We will field-test MIF by applying it to the analysis of human protein complexes that may be associated with the autoimmune disease, Alopecia Areata (Specific Aim 3). Together, MIF and its unique analysis will make available the acquisition of physiologic, human complex profiles. We propose that the patient-derived MIF data will exemplify a new strategy for analyzing these complexes, and illustrate its general applicability to many fields of study and classes of disease.

Public Health Relevance

) We will mount a new assay platform that will enable the concurrent assessment of large collections of physiologic, human protein complexes. The data generated by this methodology will be handled by novel Bioinformatics and Biostatistical analyses examining protein abundance, protein multiplicity in shared complexes, and heterotypic protein interactions. This method/analysis system will be field-tested in studies focusing on the autoimmune disease Alopecia Areata, in search of protein complex profiles with predictive value for prognosis or therapeutic response.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
7R01GM103841-06
Application #
9554217
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Smith, Ward
Project Start
2013-04-01
Project End
2019-03-31
Budget Start
2017-09-05
Budget End
2019-03-31
Support Year
6
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Missouri-Columbia
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
153890272
City
Columbia
State
MO
Country
United States
Zip Code
65211
Smith, Stephen E P; Maus, Rachel L G; Davis, Tessa R et al. (2016) Maternal IL-6 can cause T-cell-mediated juvenile alopecia by non-scarring follicular dystrophy in mice. Exp Dermatol 25:223-8
Gilhar, Amos; Schrum, Adam G; Etzioni, Amos et al. (2016) Alopecia areata: Animal models illuminate autoimmune pathogenesis and novel immunotherapeutic strategies. Autoimmun Rev 15:726-35
Schrum, Adam G; Neier, Steven C; VanHook, Annalisa M (2016) Science Signaling Podcast for 2 August 2016: Patient-specific protein complexes. Sci Signal 9:c17
Smith, Stephen E P; Neier, Steven C; Reed, Brendan K et al. (2016) Multiplex matrix network analysis of protein complexes in the human TCR signalosome. Sci Signal 9:rs7
Southwell, Amber L; Smith, Stephen E P; Davis, Tessa R et al. (2015) Ultrasensitive measurement of huntingtin protein in cerebrospinal fluid demonstrates increase with Huntington disease stage and decrease following brain huntingtin suppression. Sci Rep 5:12166
Escalante, Patricio; Peikert, Tobias; Van Keulen, Virginia P et al. (2015) Combinatorial Immunoprofiling in Latent Tuberculosis Infection. Toward Better Risk Stratification. Am J Respir Crit Care Med 192:605-17
Smith, Stephen E P; Neier, Steven C; Davis, Tessa R et al. (2014) Signalling protein complexes isolated from primary human skin-resident T cells can be analysed by Multiplex IP-FCM. Exp Dermatol 23:272-3
Neier, Steven C; Smith, Stephen E P; Davis, Tessa R et al. (2013) Toward T cell protein-protein interaction activity relevant to alopecia areata. J Investig Dermatol Symp Proc 16:S31-3